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Data vault modeling was originally conceived by Dan Linstedt in the 1990s and was released in 2000 as a public domain modeling method. In a series of five articles in The Data Administration Newsletter the basic rules of the Data Vault method are expanded and explained.
More complex systems can maintain a history and audit trail of all changes to the data loaded in the data warehouse. As the load phase interacts with a database, the constraints defined in the database schema – as well as in triggers activated upon data load – apply (for example, uniqueness, referential integrity , mandatory fields), which ...
Database auditing involves observing a database to be aware of the actions of database users. Database administrators and consultants often set up auditing for security purposes, for example, to ensure that those without the permission to access information do not access it.
In data management and data warehousing, a slowly changing dimension (SCD) is a dimension that stores data which, while generally stable, may change over time, often in an unpredictable manner. [1]
Oracle Cloud is a cloud computing service offered by ... Governance: For auditing, identity and access management, the platform has data integrity checks ...
MagicDraw provides transformation of UML models to specific XML Schema and DB models (generic and Oracle DDL) and vice versa, and any to any transformation. [ 5 ] Also model-to-model transformations between the same or different meta-models can be defined and run directly in MagicDraw by using the QVT plugin.
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Protecting the system vault is vital to the system, and improved processes must be put in place to offer database integrity and physical security. [5] The tokenization system must be secured and validated using security best practices [6] applicable to sensitive data protection, secure storage, audit, authentication and authorization. The ...